Nowadays, in the biological medical industry, life science research and agriculture animal technology, the animal locomotion analysis has become an indispensable work. In traditional locomotion analysis technology of animal behavior, most of solutions use manual method, sensor array or camera to obtain the location of a measured object, and then identifies the location of the measured object by manual analysis or automatic algorithm.
However, the manual manner not only is time-consuming and high-cost but also lack of objectivity. The use of sensor array (e.g. the resistive-type touch device or the capacitive-type touch device) would result in excessively large-sized analysis apparatus and unfriendly maintenance, and the price of such sensor array generally is expensive. Additionally, in the situation of single camera being used to obtain the location of the measured object, only the two-dimensional location of the measured object can be obtained and it is easily interfered by the light shadow change and background factors. If multiple cameras are used to obtain the location of the measured object, it is still difficult to obtain the third-dimensional location of the measured object resulting from the synchronization problem, and also is difficult to obtain the pose information of the measured object at the side facing away from the camera for pose reconstruction resulting from the limited field of view of the camera. Accordingly, it is difficult to achieve accurate 3D moving track and pose reconstruction.